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Record W2781711192 · doi:10.1152/ajpheart.00339.2017

Guidelines for measuring cardiac physiology in mice

2018· article· en· W2781711192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of Alberta
FundersHeart and Stroke Foundation of CanadaNational Heart, Lung, and Blood InstituteNational Institutes of HealthNational Institute of General Medical SciencesAmerican Heart AssociationU.S. Department of Veterans Affairs
KeywordsCardiovascular physiologyDiseaseMedicineTranslational researchPhysiologyNeuroscienceBioinformaticsIntensive care medicinePathologyCardiologyBiology

Abstract

fetched live from OpenAlex

Cardiovascular disease is a leading cause of death, and translational research is needed to understand better mechanisms whereby the left ventricle responds to injury. Mouse models of heart disease have provided valuable insights into mechanisms that occur during cardiac aging and in response to a variety of pathologies. The assessment of cardiovascular physiological responses to injury or insult is an important and necessary component of this research. With increasing consideration for rigor and reproducibility, the goal of this guidelines review is to provide best-practice information regarding how to measure accurately cardiac physiology in animal models. In this article, we define guidelines for the measurement of cardiac physiology in mice, as the most commonly used animal model in cardiovascular research. Listen to this article's corresponding podcast at http://ajpheart.podbean.com/e/guidelines-for-measuring-cardiac-physiology-in-mice/ .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.299
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it